Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add babyblueviper1/invinoveritas --skill pre-action-reviewgit clone --depth 1 https://github.com/babyblueviper1/invinoveritasWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/babyblueviper1/invinoveritas/pre-action-review)<a href="https://agentmods.dev/skills/babyblueviper1/invinoveritas/pre-action-review"><img src="https://agentmods.dev/badge/skills/babyblueviper1/invinoveritas/pre-action-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/babyblueviper1/invinoveritas/pre-action-review"><img src="https://agentmods.dev/badge/skills/babyblueviper1/invinoveritas/pre-action-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00071 | $0.00857 |
| Opus 5.5 | $0.00028 | $0.00343 |
| Sonnet 5.5 | $0.00014 | $0.00171 |
| Haiku 4.5 | $0.00007 | $0.00086 |
Grade C, and why
pre-action-review scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
- **Destructive or hard-to-reverse shell commands** — `rm -rf`, dropping a database/table, How it starts
The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pre-action review
Before you execute an action that would be hard or impossible to cleanly undo, call the
review tool (via the invinoveritas MCP connection) and pass a plain-text description of
exactly what you're about to do. It returns an independent approve / approve_with_concerns /
reject verdict with a confidence score and, on reject, specific blocking issues.
When to use this
Call it before, not after, whenever the action fits any of these:
- Destructive or hard-to-reverse shell commands —
rm -rf, dropping a database/table, force-pushing over history, deleting a cloud resource, revoking credentials. - Merges and branch operations at scale — this matters more than usual on Origin-style
workflows where many agents branch, resolve conflicts, and merge with little or no human in
the loop per merge. A signed pre-merge verdict is a real, checkable second opinion on a merge
that might otherwise go straight to
mainunreviewed. - Production deploys and migrations — anything that changes live infrastructure, schema, or configuration in a way a rollback might not cleanly reverse.
- Financial or irreversible-by-nature actions — a payment, a transfer, a trade, deleting a user's data, sending an external communication on someone's behalf.
- Anything you're not fully confident about — if you'd want a second pair of eyes on this
before running it yourself, that's the signal to call
review.
Do NOT call it for routine, easily-reversible edits (a normal code change on a feature branch, a local test run, reading a file) — that's noise, not signal, and burns the user's call budget.
How to call it
review(
artifact="<plain description of the exact action: what command/merge/deploy, on what target,
with what data at stake>",
artifact_type="general" # or "trade" / "onchain_action" for financial actions
)
Be concrete: name the actual command, the actual branch/target, and any stated safeguards (a tested backup, a dry-run result) — a vague artifact gets a vague, less useful verdict.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 69 lines · 71 tokens per session scan C 465eb4a04b1a
pre-action-review is a skill published in the GitHub repository babyblueviper1/invinoveritas (6 stars, last pushed today), licensed Apache-2.0. It adds 71 tokens to every session and 857 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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